Norwegian version
Stefano Nichele

Stefano Nichele

About

Stefano Nichele is Associate Professor at the Department of Computer Science. Nichele is the founder and deputy head of the Applied Artificial Intelligence research group. He recently started the Living Technology Lab (part of OsloMet AI Lab), where artificial life and complex systems approaches are used to understand intelligence.

Research interests:
- Artificial Life, Complex Systems, Evo-Devo, Cellular Automata
- Artificial Intelligence, Biological and Artificial Neural Networks, Deep Learning, Reservoir Computing
- Bio-inspired and Evolutionary Computation, Neuro-evolution

Personal website: http://www.nichele.eu/

Research projects

Scientific publications

Heiney, Kristine; Huse Ramstad, Ola; Fiskum, Vegard; Christiansen, Nicholas; Sandvig, Axel; Nichele, Stefano; Sandvig, Ioanna (2021). Criticality, connectivity, and neural disorder: A multifaceted approach to neural computation. Frontiers in Computational Neuroscience . Vol. 15:611183.
https://hdl.handle.net/11250/2728005

Fladby, Torgeir; Haugerud, Hårek; Nichele, Stefano; Begnum, Kyrre; Yazidi, Anis (2020). Evading a Machine Learning-based Intrusion Detection System through Adversarial Perturbations. NN, NN (Ed.). RACS '20: Proceedings of the International Conference on Research in Adaptive and Convergent Systems. Research-article. p. 161-166. Association for Computing Machinery (ACM).
https://hdl.handle.net/11250/2729788

Zhang, Jianhua; Yin, Zhong; Chen, Peng; Nichele, Stefano (2020). Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review. Information Fusion . Vol. 59.

Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (2020). EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality. Castillo, Pedro A.; Laredo, Juan Luis Jiménez; de Vega, Francisco Fernández (Ed.). Applications of Evolutionary Computation. Mangler. p. 133-148. Springer.
https://hdl.handle.net/11250/2724664

Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (2020). A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality. Cognitive Neurodynamics .
https://hdl.handle.net/11250/2657791

Valderhaug, Vibeke Devold; Heiney, Kristine; Huse Ramstad, Ola; Bråthen, Geir; Kuan, Wei-Li; Nichele, Stefano; Sandvig, Axel; Sandvig, Ioanna (2020). Criticality as a measure of developing proteinopathy in engineered human neural networks. 22 p. BioRxiv.
https://hdl.handle.net/11250/2735243

Valderhaug, Vibeke Devold; Huse Ramstad, Ola; van de Wijdeven, Rosanne Francisca; Heiney, Kristine; Nichele, Stefano; Sandvig, Axel; Sandvig, Ioanna (2020). Structural and functional alterations associated with the LRRK2 G2019S mutation revealed in structured human neural networks. 27 p. BioRxiv.
https://hdl.handle.net/11250/2735246

Mello, Gustavo; Pontes-Filho, Sidney; Sandvig, Ioanna; Valderhaug, Vibeke Devold; Zouganeli, Evi; Huse Ramstad, Ola; Sandvig, Axel; Nichele, Stefano (2020). Method to Obtain Neuromorphic Reservoir Networks from Images of in Vitro Cortical Networks. Huang, Tingwen (Ed.). Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI2019). Chapter: Neuromorphic Cognitive Computing (SNCC). p. 2360-2366. IEEE.
http://hdl.handle.net/11250/2644970

Heiney, Kristine; Huse Ramstad, Ola; Sandvig, Ioanna; Sandvig, Axel; Nichele, Stefano (2020). Assessment and manipulation of the computational capacity of in vitro neuronal networks through criticality in neuronal avalanches. Huang, Tingwen (Ed.). Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI2019). Chapter: Artificial Life (ALIFE). p. 246-253. IEEE.
https://ieeexplore.ieee.org/document/9002693

Zhang, Jianhua; Li, Jianrong; Nichele, Stefano (2020). Instantaneous Mental Workload Recognition Using Wavelet-Packet Decomposition and Semi-Supervised Learning. Huang, Tingwen (Ed.). Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI2019). KAPITTEL. p. 410-416. IEEE. 10.1109/SSCI44817.2019.9002997





These publications are obtained from Cristin. The list may be incomplete